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TensorFlow v2.3.1

TensorFlow: v2.3.1 Release

Release date:

September 22, 2020

Previous version:

v2.3.0 (released July 24, 2020)

Magnitude:

24,889 Line Impact

Contributors:

130 total committers

Data confidence:

Commits:

585

91 Features Released with v2.3.1

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v2.4.0-rc0 Released January 4, 2021

v2.3.2 Released January 4, 2021

v2.3.1 Released September 22, 2020

v2.3.0 Released July 24, 2020

v2.3.0-rc2 Released July 17, 2020

v2.3.0-rc1 Released July 8, 2020

v2.3.0-rc0 Released January 4, 2021

v2.2.2 Released January 4, 2021

Top Contributors in v2.3.1

tensorflower-gardener

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Release Notes Published

Release 2.3.1

Bug Fixes and Other Changes

Fixes an undefined behavior causing a segfault in tf.raw_ops.Switch (CVE-2020-15190)
Fixes three vulnerabilities in conversion to DLPack format (CVE-2020-15191, CVE-2020-15192, CVE-2020-15193)
Fixes two vulnerabilities in SparseFillEmptyRowsGrad (CVE-2020-15194, CVE-2020-15195)
Fixes several vulnerabilities in RaggedCountSparseOutput and SparseCountSparseOutput operations (CVE-2020-15196, CVE-2020-15197, CVE-2020-15198, CVE-2020-15199, CVE-2020-15200, CVE-2020-15201)
Fixes an integer truncation vulnerability in code using the work sharder API (CVE-2020-15202)
Fixes a format string vulnerability in tf.strings.as_string (CVE-2020-15203)
Fixes segfault raised by calling session-only ops in eager mode (CVE-2020-15204)
Fixes data leak and potential ASLR violation from tf.raw_ops.StringNGrams (CVE-2020-15205)
Fixes segfaults caused by incomplete SavedModel validation (CVE-2020-15206)
Fixes a data corruption due to a bug in negative indexing support in TFLite (CVE-2020-15207)
Fixes a data corruption due to dimension mismatch in TFLite (CVE-2020-15208)
Fixes several vulnerabilities in TFLite saved model format (CVE-2020-15209, CVE-2020-15210, CVE-2020-15211)
Fixes several vulnerabilities in TFLite implementation of segment sum (CVE-2020-15212, CVE-2020-15213, CVE-2020-15214)
Updates sqlite3 to 3.33.00 to handle CVE-2020-15358.
Fixes deprecated usage of collections API
Removes scipy dependency from setup.py since TensorFlow does not need it to install the pip package

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